The present invention relates generally to computer vision and pattern recognition, and in particular to methods of assessing the ability of a video-based system to detect the presence of fire.
The ability to detect the presence of fire is important on a number of levels, including with respect to human safety and the safety of property. In particular, because of the rapid expansion rate of a fire, it is important to detect the presence of a fire as early as possible. Traditional means of detecting fire include particle sampling (i.e., smoke detectors) and temperature sensors. While accurate, these methods include a number of drawbacks. For instance, traditional particle or smoke detectors require smoke to physically reach a sensor. In some applications, the location of the fire or the presence of ventilated air systems prevents smoke from reaching the detector for an extended length of time, allowing the fire time to spread. A typical temperature sensor requires the sensor to be located physically close to the fire, because the temperature sensor will not sense a fire until it has spread to the location of the temperature sensor. In addition, neither of these systems provides as much data as might be desired regarding size, location, or intensity of the fire.
A video-based fire detection system provides solutions to some of these problems. In particular, video-based systems can detect the presence of fire prior to physical evidence of the fire (e.g., smoke particles) reaching the video detector. However, the video-based fire detection system presents challenges not encountered in traditional sensors. For instance, the ability of a video-based system to detect the presence of fire depends, in part, on the environment in which the video detector is operating. In addition, problems associated with video quality degradation may inhibit the ability of the system to accurately detect the presence of fire.
For these reasons, it would be beneficial to develop a method of assessing the ability of a video-based system to accurately detect the presence of fire.